// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

#include "main.h"

#include <Eigen/CXX11/Tensor>

using Eigen::array;
using Eigen::Tensor;

template<int DataLayout>
static void
test_simple_shuffling()
{
	Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
	tensor.setRandom();
	array<ptrdiff_t, 4> shuffles;
	shuffles[0] = 0;
	shuffles[1] = 1;
	shuffles[2] = 2;
	shuffles[3] = 3;

	Tensor<float, 4, DataLayout> no_shuffle;
	no_shuffle = tensor.shuffle(shuffles);

	VERIFY_IS_EQUAL(no_shuffle.dimension(0), 2);
	VERIFY_IS_EQUAL(no_shuffle.dimension(1), 3);
	VERIFY_IS_EQUAL(no_shuffle.dimension(2), 5);
	VERIFY_IS_EQUAL(no_shuffle.dimension(3), 7);

	for (int i = 0; i < 2; ++i) {
		for (int j = 0; j < 3; ++j) {
			for (int k = 0; k < 5; ++k) {
				for (int l = 0; l < 7; ++l) {
					VERIFY_IS_EQUAL(tensor(i, j, k, l), no_shuffle(i, j, k, l));
				}
			}
		}
	}

	shuffles[0] = 2;
	shuffles[1] = 3;
	shuffles[2] = 1;
	shuffles[3] = 0;
	Tensor<float, 4, DataLayout> shuffle;
	shuffle = tensor.shuffle(shuffles);

	VERIFY_IS_EQUAL(shuffle.dimension(0), 5);
	VERIFY_IS_EQUAL(shuffle.dimension(1), 7);
	VERIFY_IS_EQUAL(shuffle.dimension(2), 3);
	VERIFY_IS_EQUAL(shuffle.dimension(3), 2);

	for (int i = 0; i < 2; ++i) {
		for (int j = 0; j < 3; ++j) {
			for (int k = 0; k < 5; ++k) {
				for (int l = 0; l < 7; ++l) {
					VERIFY_IS_EQUAL(tensor(i, j, k, l), shuffle(k, l, j, i));
				}
			}
		}
	}
}

template<int DataLayout>
static void
test_expr_shuffling()
{
	Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
	tensor.setRandom();

	array<ptrdiff_t, 4> shuffles;
	shuffles[0] = 2;
	shuffles[1] = 3;
	shuffles[2] = 1;
	shuffles[3] = 0;
	Tensor<float, 4, DataLayout> expected;
	expected = tensor.shuffle(shuffles);

	Tensor<float, 4, DataLayout> result(5, 7, 3, 2);

	array<ptrdiff_t, 4> src_slice_dim{ { 2, 3, 1, 7 } };
	array<ptrdiff_t, 4> src_slice_start{ { 0, 0, 0, 0 } };
	array<ptrdiff_t, 4> dst_slice_dim{ { 1, 7, 3, 2 } };
	array<ptrdiff_t, 4> dst_slice_start{ { 0, 0, 0, 0 } };

	for (int i = 0; i < 5; ++i) {
		result.slice(dst_slice_start, dst_slice_dim) = tensor.slice(src_slice_start, src_slice_dim).shuffle(shuffles);
		src_slice_start[2] += 1;
		dst_slice_start[0] += 1;
	}

	VERIFY_IS_EQUAL(result.dimension(0), 5);
	VERIFY_IS_EQUAL(result.dimension(1), 7);
	VERIFY_IS_EQUAL(result.dimension(2), 3);
	VERIFY_IS_EQUAL(result.dimension(3), 2);

	for (int i = 0; i < expected.dimension(0); ++i) {
		for (int j = 0; j < expected.dimension(1); ++j) {
			for (int k = 0; k < expected.dimension(2); ++k) {
				for (int l = 0; l < expected.dimension(3); ++l) {
					VERIFY_IS_EQUAL(result(i, j, k, l), expected(i, j, k, l));
				}
			}
		}
	}

	dst_slice_start[0] = 0;
	result.setRandom();
	for (int i = 0; i < 5; ++i) {
		result.slice(dst_slice_start, dst_slice_dim) = tensor.shuffle(shuffles).slice(dst_slice_start, dst_slice_dim);
		dst_slice_start[0] += 1;
	}

	for (int i = 0; i < expected.dimension(0); ++i) {
		for (int j = 0; j < expected.dimension(1); ++j) {
			for (int k = 0; k < expected.dimension(2); ++k) {
				for (int l = 0; l < expected.dimension(3); ++l) {
					VERIFY_IS_EQUAL(result(i, j, k, l), expected(i, j, k, l));
				}
			}
		}
	}
}

template<int DataLayout>
static void
test_shuffling_as_value()
{
	Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
	tensor.setRandom();
	array<ptrdiff_t, 4> shuffles;
	shuffles[2] = 0;
	shuffles[3] = 1;
	shuffles[1] = 2;
	shuffles[0] = 3;
	Tensor<float, 4, DataLayout> shuffle(5, 7, 3, 2);
	shuffle.shuffle(shuffles) = tensor;

	VERIFY_IS_EQUAL(shuffle.dimension(0), 5);
	VERIFY_IS_EQUAL(shuffle.dimension(1), 7);
	VERIFY_IS_EQUAL(shuffle.dimension(2), 3);
	VERIFY_IS_EQUAL(shuffle.dimension(3), 2);

	for (int i = 0; i < 2; ++i) {
		for (int j = 0; j < 3; ++j) {
			for (int k = 0; k < 5; ++k) {
				for (int l = 0; l < 7; ++l) {
					VERIFY_IS_EQUAL(tensor(i, j, k, l), shuffle(k, l, j, i));
				}
			}
		}
	}

	array<ptrdiff_t, 4> no_shuffle;
	no_shuffle[0] = 0;
	no_shuffle[1] = 1;
	no_shuffle[2] = 2;
	no_shuffle[3] = 3;
	Tensor<float, 4, DataLayout> shuffle2(5, 7, 3, 2);
	shuffle2.shuffle(shuffles) = tensor.shuffle(no_shuffle);
	for (int i = 0; i < 5; ++i) {
		for (int j = 0; j < 7; ++j) {
			for (int k = 0; k < 3; ++k) {
				for (int l = 0; l < 2; ++l) {
					VERIFY_IS_EQUAL(shuffle2(i, j, k, l), shuffle(i, j, k, l));
				}
			}
		}
	}
}

template<int DataLayout>
static void
test_shuffle_unshuffle()
{
	Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
	tensor.setRandom();

	// Choose a random permutation.
	array<ptrdiff_t, 4> shuffles;
	for (int i = 0; i < 4; ++i) {
		shuffles[i] = i;
	}
	array<ptrdiff_t, 4> shuffles_inverse;
	for (int i = 0; i < 4; ++i) {
		const ptrdiff_t index = internal::random<ptrdiff_t>(i, 3);
		shuffles_inverse[shuffles[index]] = i;
		std::swap(shuffles[i], shuffles[index]);
	}

	Tensor<float, 4, DataLayout> shuffle;
	shuffle = tensor.shuffle(shuffles).shuffle(shuffles_inverse);

	VERIFY_IS_EQUAL(shuffle.dimension(0), 2);
	VERIFY_IS_EQUAL(shuffle.dimension(1), 3);
	VERIFY_IS_EQUAL(shuffle.dimension(2), 5);
	VERIFY_IS_EQUAL(shuffle.dimension(3), 7);

	for (int i = 0; i < 2; ++i) {
		for (int j = 0; j < 3; ++j) {
			for (int k = 0; k < 5; ++k) {
				for (int l = 0; l < 7; ++l) {
					VERIFY_IS_EQUAL(tensor(i, j, k, l), shuffle(i, j, k, l));
				}
			}
		}
	}
}

template<int DataLayout>
static void
test_empty_shuffling()
{
	Tensor<float, 4, DataLayout> tensor(2, 3, 0, 7);
	tensor.setRandom();
	array<ptrdiff_t, 4> shuffles;
	shuffles[0] = 0;
	shuffles[1] = 1;
	shuffles[2] = 2;
	shuffles[3] = 3;

	Tensor<float, 4, DataLayout> no_shuffle;
	no_shuffle = tensor.shuffle(shuffles);

	VERIFY_IS_EQUAL(no_shuffle.dimension(0), 2);
	VERIFY_IS_EQUAL(no_shuffle.dimension(1), 3);
	VERIFY_IS_EQUAL(no_shuffle.dimension(2), 0);
	VERIFY_IS_EQUAL(no_shuffle.dimension(3), 7);

	for (int i = 0; i < 2; ++i) {
		for (int j = 0; j < 3; ++j) {
			for (int k = 0; k < 0; ++k) {
				for (int l = 0; l < 7; ++l) {
					VERIFY_IS_EQUAL(tensor(i, j, k, l), no_shuffle(i, j, k, l));
				}
			}
		}
	}

	shuffles[0] = 2;
	shuffles[1] = 3;
	shuffles[2] = 1;
	shuffles[3] = 0;
	Tensor<float, 4, DataLayout> shuffle;
	shuffle = tensor.shuffle(shuffles);

	VERIFY_IS_EQUAL(shuffle.dimension(0), 0);
	VERIFY_IS_EQUAL(shuffle.dimension(1), 7);
	VERIFY_IS_EQUAL(shuffle.dimension(2), 3);
	VERIFY_IS_EQUAL(shuffle.dimension(3), 2);

	for (int i = 0; i < 2; ++i) {
		for (int j = 0; j < 3; ++j) {
			for (int k = 0; k < 0; ++k) {
				for (int l = 0; l < 7; ++l) {
					VERIFY_IS_EQUAL(tensor(i, j, k, l), shuffle(k, l, j, i));
				}
			}
		}
	}
}

EIGEN_DECLARE_TEST(cxx11_tensor_shuffling)
{
	CALL_SUBTEST(test_simple_shuffling<ColMajor>());
	CALL_SUBTEST(test_simple_shuffling<RowMajor>());
	CALL_SUBTEST(test_expr_shuffling<ColMajor>());
	CALL_SUBTEST(test_expr_shuffling<RowMajor>());
	CALL_SUBTEST(test_shuffling_as_value<ColMajor>());
	CALL_SUBTEST(test_shuffling_as_value<RowMajor>());
	CALL_SUBTEST(test_shuffle_unshuffle<ColMajor>());
	CALL_SUBTEST(test_shuffle_unshuffle<RowMajor>());
	CALL_SUBTEST(test_empty_shuffling<ColMajor>());
	CALL_SUBTEST(test_empty_shuffling<RowMajor>());
}
